Mann-Whitney U Test

Mann-Whitney U Test

The Mann-Whitney U test, also known as the Mann-Whitney-Wilcoxon test, is a statistical method used to compare two independent samples. It was developed in 1947 by Henry Mann and Donald Whitney, and is an alternative to the independent samples t test when the data is not normally distributed. The Mann-Whitney U test can be used to evaluate the significance of differences between two sets of data, such as intelligence test scores.

Assessment of intellectual abilities is an important tool in psychology and medicine. Intelligence tests are standardized methods for assessing a person's intellectual abilities and are commonly used to diagnose mental retardation and evaluate mental disorders. The most famous of these tests are the Wechsler tests for determining the general mental development of adults and children, as well as the Stanford-Binet scale.

When using tests for intellectual development, there is often a need to compare the results of two independent samples of people, for example, the results of testing two groups of patients. In this case, the Mann-Whitney U test can be a useful tool to determine whether there are significant differences between the two groups.

The Mann-Whitney U test is based on the rank values ​​of sample data, that is, their order, without taking into account their exact values. The test compares the rank sums of two samples and determines how likely it is that the sums would be the same if the two samples were from the same distribution. If the probability of this is low, then we can conclude that the two samples are statistically significantly different.

The Mann-Whitney U test does not require the assumption of normal distribution of the data and can be used for any type of data, including ordinal, nominal, and interval data. However, it is ineffective for large samples because its accuracy decreases as the sample size increases.

In conclusion, the Mann-Whitney U test is a useful statistical method for comparing two independent samples, including intelligence test scores. It allows you to determine whether there are statistically significant differences between two samples without requiring the assumption of normal distribution of the data.

The Mann-Whitney U test, also known as the Mann-Whitney-Wilcoxon test, is a statistical method used to compare two samples. This test was proposed by American statisticians Henry Mann and Donald Whitney in 1947.

The Mann-Whitney U test can be used to test the hypothesis that two samples are drawn from the same distribution. It can be used when the data is not normally distributed or when the samples are of different sizes.

Consider an example of using the Mann-Whitney U test to compare the results of two different intelligence tests. Let's say we administered two intelligence tests to two groups of people and want to find out whether there is a significant difference between the test results.

To perform a Mann-Whitney U test, you must first combine the data from both samples into one series, then rank them in ascending order and assign a rank to each value. The U value is then calculated, which is the smaller of the two sums of the ranks of each sample. The U value can be used to assess the significance of differences between samples.

If the U value is less than the critical value, then we can conclude that the differences between the samples are statistically significant. Otherwise, the differences between samples are not statistically significant.

The Mann-Whitney U test can be especially useful in cases where samples have different sizes or when the data is not normally distributed. It can be used to analyze various types of data, including quantitative, ordinal, and nominal.

In conclusion, the Mann-Whitney U test is a powerful tool for statistical data analysis and can be used to compare two samples. It can be especially useful in cases where the data does not satisfy the conditions of a normal distribution or when the samples have different sizes.

Mann-Whitney test

Modern science often uses statistical indicators to determine a particular phenomenon. Many methods have been developed, some of which are designed to identify correlations. The most famous is the Mann–Whitney U test. It can be used to compare two independent samples. To obtain conclusions, mathematical processing is carried out.

Calculation formula

It is also possible to determine the presence of a connection without calculating the coefficient K. The obtained result is compared with the normative values ​​of two samples:

up to 50 - no connection;